Greater RWE sophistication, greater privacy
This is the third in a five-part blog series focusing on how life sciences companies can establish leadership in the field by leveraging RWE sophistication.
Increasing leverage of electronic health records (EHRs), imaging systems, and social media is delivering groundbreaking patient-centric insight like never before. But as companies seek a deeper understanding of health outcomes via patient-level data, privacy-enhancing capabilities are becoming not only an imperative but also a critical source of leadership. These same capabilities are key to unlocking the full value of real-world evidence (RWE).
In our previous blog posts, we introduced four considerations life sciences companies should keep the top of mind when building an RWE ecosystem. We also discussed the first of the considerations in this blog post: Better research demands better privacy.
Today’s post focuses on the next consideration – greater RWE sophistication, greater privacy.
The ever increasing electronic capture of healthcare data is a core driver in the expanding business impact of RWE, enabling companies to improve decision making across drug development. Through comprehensive data platforms that link information from multiple sources, such as EHRs, claims databases, prescription data, lab results and social media networks, companies are gaining an unparalleled 360-degree view of treatment patterns and patient outcomes. However, even leading companies with established comprehensive RWE networks and data platforms are only beginning to realize the full potential, worth billions of dollars to pharma.
RWE efforts initially focused on claims and pharmacy datasets, with limited data variety and scenarios to uniquely identify a particular individual. In these cases, basic masking techniques were sufficient to de-identify, using suppression to remove key identifiers.
Today, as companies build access to a far greater volume and a variety of real-world data (RWD), there is potential for a high degree of sensitive information to be processed, which, if not dealt with correctly, could impact patient privacy. Executives driving RWE strategies must pay close attention to privacy compliance or run the risk of exposing their organization to the increasing financial penalties associated with breaches, as well as consequent reputational damage.
The answer to mastering privacy does not lie in more use of masking, which either negates the analytic potential of data or fails to ensure sufficient anonymity. Masking all indirect or quasi-identifiers, for example, age, gender, geographic location or specific moments in time, destroys utility for healthcare research. Conversely, not masking other potentially sensitive information, such as dates or rare diagnoses, means it may be possible to re-identify a person using a unique set of values.
Indeed, the combination of more complex data, stricter privacy regulations and de-identification guidelines, and increasing availability of public data and sophistication in cyber attacks that can lever that data have all exposed commonly used masking or typical home-grown internal privacy techniques as antiquated methods and tools. It is only through more sophisticated, risk-based privacy-enhancing techniques that produce high-quality de-identified data, that healthcare organizations can meet new privacy standards such as the EU General Data Protection Regulation (GDPR), and unlock the full potential of groundbreaking RWE sophistication.
Watch for the next post in this series, which will take a closer look at the consideration of moving from blunt tools to risk-based privacy techniques. But in the meantime, don’t miss our webinar with IMS Brogan, Experiences Building an RWE Database.
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